American Institute of Certified Planners (AICP) Practice Exam

In systematic sampling, subjects are selected by taking every nth individual from a population after choosing a random starting point. This method provides a structured way of sampling that can help ensure that the sample is evenly distributed across the population.

The process begins by determining the sample size needed and then dividing the total population size by that sample size to find the sampling interval (n). For example, if you have a population of 100 and want a sample of 10, you would select every 10th individual. After selecting a random starting point, usually between 1 and n, subsequent selections would follow the systematic rule.

This approach balances randomness and structure, reducing potential bias while also making the sampling process simpler and easier to implement. It contrasts with methodologies such as convenience sampling, which does not ensure an even representation of the population, or sampling based purely on specific characteristics, which could introduce bias. Random selection is a method that doesn't inherently provide the structured interval-based approach found in systematic sampling.